JP4833043B2 - Affinity device using blog or query click - Google Patents

Description

  The present invention relates to an affinity device using a blog or a query click. More specifically, the present invention relates to an apparatus and a method for extracting information on related products from a click history searched by a blog site on the Internet or a user.

  As various search services and online shopping using the Internet become widespread, not only products requested by users but also products and services related to those products are widely presented to users. . For example, when a user searches an Internet shopping site for a desired book, the system of the shopping site detects not only the information of the book but also another user who purchased the same book, and the other user purchased it. Display books at the same time and try to link them to the sale of related books.

Also, for example, in Patent Document 1, customer purchase history data is acquired, and from this purchase history data, the degree of recommendation of each product is obtained from the activity level of the product and the purchase frequency of each product, and the customer purchases the product. In such a case, a product recommendation device or the like that recommends a product having a high recommendation degree among products having a time-series order relationship with the product is disclosed.
JP 2002-279279 A

  In the example of the above-mentioned shopping site for books, other products are recommended using the book purchase history of other users, but related products cannot be recommended from categories not related to books. . There are sites that offer similar services in addition to books, but product information other than products handled outside the site cannot be recommended.

  In the method described in Patent Document 1, a large number of user (customer) purchase histories are accumulated in time series, and related products are extracted and recommended. However, in such a method, there is a case where a user who does not have a purchase history or a product which is not yet released such as a new product has little data accumulation and may not always be effective. Also, in recent times when there are an enormous number of products, and the trends and changes are intense, the range of products that can be recommended only by accumulating user purchase histories tends to be narrow. This is because a user's willingness to purchase a product cannot be determined only by past user histories, and is also influenced by the situation in the world and trends of other users.

  In view of the above-mentioned problems, the present invention effectively utilizes resources such as various databases already realized on the Internet and obtains related products from sites that react sensitively to the world situation and fashion. It is an object to provide a new device that can be extracted and recommended.

  The present invention provides the following solutions.

(1) In the bidding or product search of an auction on the Internet, acquiring the product information selected by the user from the user terminal and acquiring the first product information of the product requested by the user;
Obtaining a page related to the first product information from a site different from the auction site or the product search site, and analyzing the characteristics of the related page;
Extracting second product information that frequently appears in the page obtained by the analysis;
Obtaining a degree of conformity between the second product information and the product information for sale stored in the product description database;
Determining the second product information whose fitness is higher than a predetermined value as a recommended product related to the first product information;
Including methods.

  In this method, first, the product name or keyword of the product selected by the user when the user performs an auction or product search on the Internet is acquired as the first product information. Next, a page related to the first product information is acquired from a site different from the site used for the auction site or product search (for example, a blog site or another site browsed by a user who searches for the same product), Features are analyzed for this related page. Then, second product information (product name, keyword) that frequently appears in the page obtained by the analysis is obtained. Then, the degree of matching between the second item information and the sale item information stored in the item description database is obtained, and the second item information having a high degree of matching is determined as a recommended item for the user.

  By doing in this way, the width | variety of the recommendation goods with respect to a user can be widened using the information of the other page different from the page which the user referred directly. That is, related products can be extracted using indirect information.

(2) An apparatus for extracting information on other products related to the product requested by the user,
A user-selected product information acquisition unit that acquires product information selected by the user and acquires a product keyword from the product information in an auction bid or product search from a user terminal;
A blog search unit that searches a blog site on the network based on the product keyword;
A keyword product name extraction unit that extracts keywords of product names that frequently appear in the content page from the blog content obtained by the blog search unit;
An extracted keyword / product DB matching unit that compares the extracted keyword with the product information for sale stored in the product description database and obtains the degree of fit;
A recommended product determination unit that determines a product keyword having a higher fitness than a predetermined value as a recommended product for the user;
A device comprising:

  According to such a configuration, the device acquires the product information selected by the user in the bidding for the auction or the product search on the Internet from the user terminal, and acquires the product keyword from the product information. Next, a search is performed for a blog site on the network using the product keyword. From the obtained blog content, extract the keyword of the product name that appears frequently on the content page, and store it in the extracted keyword and product description database (typically provided by the product manufacturer or seller) The product information for sale is compared, the degree of matching is obtained, and a product keyword having a degree of matching higher than a predetermined value is determined as a recommended product for the user.

  By doing in this way, it is possible to extract recommended products using various information (for example, word-of-mouth information described in a charisma blog) obtained from blogs with high advertising effectiveness that exist on the Internet. .

(3) An apparatus for extracting information on other products related to the product desired by the user,
A user-selected product information acquisition unit that acquires product information selected by the user and acquires a product keyword from the product information in an auction bid or product search from a user terminal;
A click page acquisition unit for acquiring a page different from the product information page clicked by another user who clicked the same page as the product information page clicked by the user;
Another product keyword extraction unit that extracts keywords of other products that frequently appear on the different page;
A product DB / click page matching unit for determining the degree of matching between the keyword of the other product and the product information for sale stored in the product description database;
A recommended product determining unit that determines product information whose fitness is higher than a predetermined value as a recommended product related to the product requested by the user;
A device comprising:

  According to such a configuration, the apparatus acquires the product information selected by the user in the bidding for the auction on the Internet or the product search from the user terminal, and acquires the product keyword from the product information. Next, a page different from the product information page clicked by another user who clicked the same page as the product information page clicked by the user is extracted. Then, keywords of other products that frequently appear on this other page are extracted, the degree of matching between the sales product information stored in the product description database and the other page is obtained, and the degree of matching is higher than a predetermined value The product information is determined as a recommended product related to the product requested by the user.

  By doing in this way, another user who clicked the same page as the page clicked by the user during auction bidding or product search can extract recommended products using information on another page clicked Can do.

  (4) The device according to (2) or (3), wherein the keyword of the frequently appearing product is obtained by calculating a TF * IDF value.

  According to such a configuration, a TF * IDF value is obtained in order to extract frequently occurring words from the acquired blog page or a page clicked by another user. The TF * IDF value is a widely known method for extracting words that frequently appear on a specific page, and is therefore useful for extracting features of a blog page or a clicked page.

  (5) The product information page clicked by another user who clicked the same page as the reference news page or reference article page referred to by the user instead of the product information page clicked by the user. The apparatus according to (3), wherein another page is extracted.

  According to such a configuration, this apparatus can use a history of actions based on personal interests such as a reference news page history and a reference article instead of the product information page clicked by the user. By doing in this way, the user who clicked the page of the same interest can be regarded as a similar user, and information can also be extracted from other pages clicked by these users.

  According to the present invention, resources that are realized on the Internet are effectively used, and in particular, information and history created by an unrelated person who is completely different from the user who searches are used to extract and recommend related products. It is possible to provide such a device.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[Embodiment 1]
FIG. 1 is a block diagram of an affinity apparatus 10 and related systems according to Embodiment 1 of the present invention. The affinity device 10 of the present invention is a device for providing other product information related to a product to a user using various information on the Internet. The affinity device 10 includes a user terminal 30 that is a user's terminal via the Internet 40, 50, a search device 20 including a search engine that searches a Web page on the Internet, and various product information sites that provide detailed product information. 51 (typically including a product description DB 52) and various blog sites 53. Here, the user (user) uses the user terminal 30 to try to display a product that is being purchased by some means. For example, a product search result is clicked to display product information, or target product information is displayed from a bid screen on an auction site.

  The affinity device 10 includes a user-selected product information acquisition unit 11, a blog search unit 12, a keyword product name extraction unit 13, an extraction keyword / product DB matching unit 14, and a recommended product determination unit 15. In addition, a profile DB 16 that stores user history and various personal information and a blog DB 17 that is used for blog-specific searches are provided. However, although the profile DB 16 and the blog DB 17 may be provided inside the apparatus, they may be provided in an external apparatus connected to the network. The function of each part will be described with reference to FIG.

  The search device 20 is communicably connected to the affinity device 10 and typically includes a query reception unit 21, a query transmission unit 22, a search processing unit 23, a search result generation unit 24, a search result transmission unit 25, and a search log storage. Part 26 is provided. Here, the query refers to receiving a query from the user or another device (here, the affinity device 10) and returning the result. The search processing unit 23 performs an actual search process using the search keyword and the search condition input from the query receiving unit 21, and here, a known search technique may be used. The search result generation unit 24 and the search result transmission unit 25 process the search result according to the request of the query, generate a display screen so that the user can easily see, and transmit the result to the request source. . The WEB page DB 27 is a database that stores information for search. If the WEB page DB 27 is connected to the search device 20 in some form, this database can be stored inside or outside the search device 20. Good. In the affinity device 10 and the search device 20, the above configuration is only an example, and it goes without saying that various other variations are possible.

  FIG. 2 is a diagram illustrating a processing flow performed by the affinity device 10 according to the first embodiment of the present invention. First, in step S1, the user-selected product information acquisition unit 11 performs a Yahoo! Various auction sites on the Internet such as auctions, Yahoo! Product information desired to be purchased is acquired through various product information searches such as product search. For example, in the auction, product names and keywords are acquired from screen information to be bid, and in Internet shopping from product purchase screen information. In the present invention, an arbitrary method may be used as a method for acquiring a product name or a keyword to be purchased instead of the main point.

  Next, in step S2, the blog search unit 12 that plays a central role in the first embodiment searches for a large number of blog sites 53 on the Internet using the product names obtained above. A blog is generally a diary-like home page created by various users on the Internet, but is now attracting attention as an advertising means for products. For example, an advertising service company pays blog creators (bloggers), puts their experiences on using products of customer companies on their blogs, and so on. This is because it is not uncommon for a human-made blog site called Charisma Broga to have tens of thousands of visitors every day. This is also called Verval Marketing, and is a new PR technique that uses word-of-mouth. Word-of-mouth is considered to be highly effective in advertising as a reflection of the voice and boom of users, and a blog on the Internet is very useful as a means of posting such word-of-mouth information. In the present invention, a blog is used as a means for obtaining related product information. The blog DB 17 in FIG. 1 is a blog-dedicated database that stores a large number of links to such blog sites. Using this database, the blog search unit 12 can efficiently collect blog pages on which product names and keywords that the user wants to purchase are posted.

  Next, in step S <b> 3, the keyword product name extraction unit 13 analyzes the collected blog pages, and extracts the product name as a keyword from the blog article and the comment. This keyword product name is not limited to the official name of the product itself, but may be a nickname often used for an abbreviation or a bag. Blogs are the best way to extract such keyword product names. The keyword product name extracts words that appear frequently on a specific page. Specifically, it can be obtained by calculating a TF * IDF (Term Frequency * Inverse Term Frequency) value for each word.

  Next, in step S4, the extracted keyword / product DB matching unit 14 performs matching (comparison) between the extracted keyword and the product information acquired from the product DB. The matching here is determined by obtaining a matching relationship between the extracted keyword and the product description. Here, a publicly known technique may be used for the calculation of the fitness (see, for example, Japanese Patent Publication No. 2003-167920).

  Finally, in step S5, the recommended product determination unit 15 determines a product having a high fitness from the related products as a recommended product. The above steps will be described more specifically with reference to FIG.

  FIG. 3 is a diagram illustrating an example of a table stored in the profile DB 16 according to the first embodiment of the present invention. This table stores a profile for each user. Here, first, the word “KKK camera” obtained from the page of the product that is considered for purchase by the user with the user ID “AAA” by auction bidding or product search is stored as a product keyword in this table. Is done. Based on the product keyword, the blog search unit 12 stores the URL of the blog page including the keyword. As a keyword at this time, not only “KKK camera” but also a synonym thereof may be used. For example, “KKK camera”, “Camera KKK”, and the like.

  Next, the keyword product name extraction unit 13 analyzes the contents of the collected blog pages, and uses a TF * IDF method or the like for each URL to search for words frequently appearing on a specific page as “keyword / “Product name” is extracted. Here, it is assumed that “AAY lens”, “QQQ printer”, and “MMM binoculars” are extracted.

  The extracted keyword / product DB matching unit 14 compares the extracted keyword / product name with the official product name stored in the product description DB, and extracts the official product name having a high degree of matching. Here, “MMM binoculars” is described as the product name in the product DB as it is, and therefore extracted as the fitness 100. On the other hand, “AAA lens” and “ZZZ printer” have a slightly low degree of matching with “keyword / product name”, which are 86.0 and 54.0, respectively.

  FIG. 4 is a diagram illustrating a display example of related product information on the auction bid screen. In this screen display, the left area and the upper right area are normal auction bid screens. The user who has displayed this screen considers whether or not he / she wants to bid for “KKK camera” which is a product exhibited by the seller “kana”. The area at the lower right of the screen (indicated by reference numeral 60) is related product information added by the affinity device 10. In this area, other recommended products from the information on the blog are described as “People who are discussing this product are also discussing such products”, “MMM binoculars”, “AAA lenses”, “ZZZ printers” Are listed in descending order of fitness. Although not shown here, the name of a popular mblog may be displayed as an information source. Useful for advertisers of "MMM Camera" if the user is guided to "MMM Binoculars" as well as "KKK Camera" by referring to related product information based on information obtained from this blog It is. In this way, display of related products using a blog has never existed, and it can be said that this is a new advertising means for related products aimed at the advertising effect of word of mouth.

[Embodiment 2]
FIG. 5 is a block diagram of the affinity device 10a and related systems according to the second embodiment of the present invention. In the present embodiment, the affinity device 10a provides the user terminal 30 that is a user's terminal via the Internet 40, 50, the search device 20 including a search engine that searches the Internet, and the detailed information of the product. Connected to various product information sites 51 (including a product description DB 52). Such a system configuration is the same as that in FIG. 1, but the difference from FIG. 1 is that the blog search unit 12 has been replaced with the click page acquisition unit 12a, the blog site 53 and the blog DB 17 exist. Instead, there is a user click history DB 17a and a reference news page history DB 17b.

  The affinity device 10a includes a user-selected product information acquisition unit 11a, a click page acquisition unit 12a, another product keyword extraction unit 13a, a product DB / click page matching unit 14a, and a recommended product determination unit 15a. Further, the profile DB 16, the user click history DB 17a, and the like may be provided inside the apparatus or may be provided outside connected to the network. The operation of each part of the affinity device 10a will be described with reference to FIG.

  The search device 20 is communicably connected to the affinity device 10a, and typically includes a query reception unit 21, a query transmission unit 22, a search processing unit 23, a search result generation unit 24, a search result transmission unit 25, and a search log storage. Part 26 is provided. Since the configuration of the search device 20 is exactly the same as that in FIG. 1, the description thereof is omitted here. In the affinity device 10a and the search device 20, the above configuration is only an example, and it is needless to say that various other configurations are possible.

  FIG. 6 is a diagram illustrating a processing flow performed by the affinity device 10a according to the second embodiment of the present invention. First, in step S1a, the user-selected product information acquisition unit 11a performs a Yahoo! The product information (product name, etc.) of the product that the user intends to purchase is acquired through various auction sites on the Internet such as an auction and various product information searches. For example, a product name or the like is acquired from a bid page in an auction or from a purchase page in Internet shopping. Here, the method for obtaining the name of a product to be purchased may be arbitrary.

  Step S1a is processing when the user has an intention to purchase a product, but in a general search, the purpose is not necessarily the purchase of the product. In this case, in step S1b instead of step S1a, the Web page obtained by the general search is acquired.

  Next, in step S2a, the click page acquisition unit 12a acquires the URL of the bid page of the auction, the URL of the product page searched for the product, or the URL of the page clicked by the user as a result of the general search. This URL is stored in the profile DB 16a as a user profile click history. Further, the click page acquisition unit 12a finds out the user ID that clicked the same URL from the click history stored in the user profile. Click history of all users can be acquired from the user click history DB 17a. A method for automatically collecting user click histories is a known technique. However, in order to collect the reference news page history, the click page acquisition unit will need to search the user terminal 30 periodically.

  Next, in step S3a, the other product keyword extraction unit 13a analyzes the page content of the URL clicked by the other user from the click history of the other user, and extracts a word serving as a feature (profile). The characteristic word may be an official name of a product, a nickname often used for an abbreviation or a bag. Specifically, it can be obtained by calculating a TF * IDF value for each word.

  Next, in step S4a, the product DB / click page matching unit 14a performs matching (comparison) between the product information stored in the product description DB and the profile (word that is characteristic) of the page clicked by another user. . The matching here is determined by obtaining the fitness. Here, a known technique may be used for the calculation of the fitness.

  Finally, in step S5a, the recommended product determination unit 15a recommends a word having a high degree of matching with the product keyword searched by the original user from among the characteristic words extracted from pages clicked by other users. Determine as a product. The above steps will be specifically described with reference to FIG.

  FIG. 7 is a diagram illustrating an example of a table stored in the profile DB 16 according to the second embodiment of the present invention. Here, first, “KKK camera” searched for by the user with the user ID “AAA” is stored in this table as “product keyword”. At this time, the URL of the product information page of “KKK camera” clicked by the user is stored in this table as the click page URL. Then, IDs of other users who clicked on the same URL (http://www.xxx.aaa) (“CCC”, “DDD”, “EEE”) are set as “similar user IDs that clicked on the same page”. Store in this table. A list of URLs of other pages clicked by these other similar users is further stored in this table.

  Next, the other product keyword extraction unit 13a searches the contents of the URL destination using the collected URL list of similar users clicked, and frequently appears on a specific page using the TF * IDF method or the like. Are extracted as recommended product candidates. At this time, instead of the clicked page, a history based on personal interests such as a reference news page history and a reference article history may be used. Here, “EEE binoculars” is extracted from the three URLs clicked by the user “CCC” and stored in the table as recommended product candidates. Similarly, “EEE binoculars” is detected from the click history of the user ID “DDD”, and “FFF lens” is extracted as a recommended product candidate from the click history of the user ID “EEE”. .

  FIG. 8 is a diagram illustrating a display example of related product information on the product search screen. In this screen display, the left region and the upper right region are screens that display specific products as a result of normal product search. This user is currently displaying the screen of the product “KKK camera”, and the area at the lower right of the screen is related product information added by the affinity device 10a. Here, in the area indicated by reference numeral 60a, as a product recommended from the information of another user, “A person searching for this product is also searching for such a product” is displayed. Links such as “binoculars” and “FFF lenses” are displayed. Here, the user name may not be particularly displayed. It is useful for advertisers of “EEE binoculars” if they can be guided not only to “KKK camera” but also “EEE binoculars” by referring to this related product information. The method of extracting related product information from the click history of other users who are interested in the same product in this way is a method that has not existed before, and can be said to be “Marketing” using indirect information of another person.

[Hardware configuration of affinity device]
FIG. 9 is a diagram illustrating an example of a hardware configuration of the affinity devices 10 and 10a according to the first and second preferred embodiments of the present invention (hereinafter simply referred to as the affinity device 10).

  The affinity device 10 includes a central processing unit (CPU) 1010 (a plurality of CPUs such as the CPU 1012 may be added in a multiprocessor configuration), a bus line 1005, a communication I / F 1040, a main memory 1050, and a BIOS. (Basic Input Output System) 1060, a USB port 1090, an I / O controller 1070, input means such as a keyboard and mouse 1100, and a display device 1022.

  Storage means such as a tape drive 1072, a hard disk 1074, an optical disk drive 1076, and a semiconductor memory 1078 can be connected to the I / O controller 1070.

  The BIOS 1060 stores a boot program executed by the CPU 1010 when the affinity device 10 is started up, a program depending on the hardware of the affinity device 10, and the like.

  The hard disk 1074 constituting the storage unit 107 stores various programs for the function of the affinity device 10 and programs for executing the functions of the present invention, and can further configure various databases as necessary.

  As the optical disc drive 1076, for example, a DVD-ROM drive, a CD-ROM drive, a DVD-RAM drive, or a CD-RAM drive can be used. In this case, the optical disk 1077 corresponding to each drive is used. A program or data may be read from the optical disk 1077 by the optical disk drive 1076 and provided to the main memory 1050 or the hard disk 1074 via the I / O controller 1070. Similarly, the tape medium 1071 corresponding to the tape drive 1072 can be used mainly for backup.

  The program provided to the affinity device 10 is provided by being stored in a recording medium such as the hard disk 1074, the optical disk 1077, or a memory card. This program may be installed in the affinity device 10 and executed by being read from the recording medium via the I / O controller 1070 or downloaded via the communication I / F 1040.

  The aforementioned program may be stored in an internal or external storage medium. Here, as a storage medium constituting the storage unit 107, in addition to the hard disk 1074, the optical disk 1077, or the memory card, a magneto-optical recording medium such as an MD, or a tape medium can be used. Further, a storage device such as a hard disk 1074 or an optical disk library provided in a server system connected to a dedicated communication line or the Internet may be used as a recording medium, and the program may be provided to the affinity device 10 via the communication line.

  Here, the display device 1022 displays a screen for accepting data input to the user or displays a calculation result screen by the affinity device 10. The display device 1022 is a cathode ray tube display device (CRT), a liquid crystal display device ( LCD).

  Here, the input means accepts input by the user, and may be configured by a keyboard, a mouse 1100, and the like.

  The communication I / F 1040 is a network adapter that enables the affinity device 10 to be connected to a terminal via a dedicated network or a public network. The communication I / F 1040 may include a modem, a cable modem, and an Ethernet (registered trademark) adapter.

  In the above example, the affinity device 10 has been mainly described. However, the functions described above can be realized by installing a program in a computer and operating the computer as a server device. Therefore, the functions realized by the server described as an embodiment in the present invention can be realized by executing the above-described method by the computer, or by introducing the above-mentioned program into the computer and executing it. It is.

  As mentioned above, although embodiment of this invention was described, this invention is not restricted to embodiment mentioned above. The effects described in the embodiments of the present invention are only the most preferable effects resulting from the present invention, and the effects of the present invention are limited to those described in the embodiments of the present invention. is not.

1 is a block diagram of an affinity device 10 and a related system according to Embodiment 1 of the present invention. It is a figure which shows the processing flow which the affinity apparatus 10 which concerns on Embodiment 1 of this invention performs. It is a figure which shows the example of the table stored in profile DB16 in Embodiment 1 of this invention. It is a figure which shows the example of a display of the related merchandise information on an auction bid screen. It is a block diagram of the affinity apparatus 10a which concerns on Embodiment 2 of this invention, and a related system. It is a figure which shows the processing flow which the affinity apparatus 10a which concerns on Embodiment 2 of this invention performs. It is a figure which shows the example of the table stored in profile DB16 in Embodiment 2. FIG. FIG. 8 is a diagram illustrating a display example of related product information on the product search screen. It is a figure which shows an example of the hardware constitutions of the affinity apparatuses 10 and 10a which concern on suitable Embodiment 1, 2 of this invention.

Explanation of symbols

10, 10a Affinity device 11, 11a User-selected product information acquisition unit 12 Blog search unit 12a Click page acquisition unit 13 Keyword product name extraction unit 13a Other product keyword extraction unit 14 Extraction keyword / product DB matching unit 14a Product DB / click page matching Section 15, 15a Recommended product determination section 16, 16a Profile DB
17 Blog DB
17a User click history DB
17b Reference news page history DB
DESCRIPTION OF SYMBOLS 20 Search apparatus 21 Query reception part 22 Query transmission part 23 Search processing part 24 Search result generation part 25 Search result transmission part 26 Search log memory | storage part 27 WEB page DB
30 User terminal 40, 50 Internet 51 Product information site 52 Product description DB
53 Blog site 60, 60a Recommended product information

Claims (4)

A device that extracts information on other products related to the product desired by the user,
A user-selected product information acquisition unit that acquires product information selected by the user and acquires a product keyword from the product information in an auction bid or product search from a user terminal;
A blog search unit that searches a blog site on the network based on the product keyword;
A keyword product name extraction unit that extracts keywords of product names that frequently appear in the content page from the blog content obtained by the blog search unit;
An extracted keyword / product DB matching unit that compares the extracted keyword with the product information for sale stored in the product description database and obtains the degree of fit;
A recommended product determination unit that determines a product keyword having a higher fitness than a predetermined value as a recommended product for the user;
A device comprising: A device that extracts information on other products related to the product desired by the user,
A user-selected product information acquisition unit that acquires product information selected by the user and acquires a product keyword from the product information in an auction bid or product search from a user terminal;
A click page acquisition unit for acquiring a page different from the product information page clicked by another user who clicked the same page as the product information page clicked by the user;
Another product keyword extraction unit that extracts keywords of other products that frequently appear on the different page;
A product DB / click page matching unit for determining the degree of matching between the keyword of the other product and the product information for sale stored in the product description database;
A recommended product determining unit that determines product information whose fitness is higher than a predetermined value as a recommended product related to the product requested by the user;
A device comprising: Keyword products for the frequent is determined by calculating the TF * IDF value, according to claim 1 or 2. The click page acquisition unit is different from the product information page clicked by another user who clicked the same page as the reference news page or reference article page referred to by the user instead of the product information page clicked by the user. The apparatus according to claim 2 , wherein:

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